Overview

Dataset statistics

Number of variables19
Number of observations1000
Missing cells706
Missing cells (%)3.7%
Total size in memory3.4 MiB
Average record size in memory3.5 KiB

Variable types

Numeric1
Text18

Alerts

subpropertyname has 701 (70.1%) missing valuesMissing
0 has unique valuesUnique
acres has unique valuesUnique
cemsid has unique valuesUnique
system has unique valuesUnique
multipolygon has unique valuesUnique

Reproduction

Analysis started2023-12-09 21:16:42.423136
Analysis finished2023-12-09 21:16:44.215346
Duration1.79 second
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean500.5
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-09T21:16:44.336307image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.95
Q1250.75
median500.5
Q3750.25
95-th percentile950.05
Maximum1000
Range999
Interquartile range (IQR)499.5

Descriptive statistics

Standard deviation288.8194361
Coefficient of variation (CV)0.5770618104
Kurtosis-1.2
Mean500.5
Median Absolute Deviation (MAD)250
Skewness0
Sum500500
Variance83416.66667
MonotonicityStrictly increasing
2023-12-09T21:16:44.508392image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
672 1
 
0.1%
659 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
662 1
 
0.1%
663 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
ValueCountFrequency (%)
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%

acres
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size65.8 KiB
2023-12-09T21:16:44.826649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length10
Mean length10.234
Min length4

Characters and Unicode

Total characters10234
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row0.04172676
2nd row0.3834388
3rd row0.98795811
4th row1.16915488
5th row0.98549465
ValueCountFrequency (%)
0.49591979 1
 
0.1%
0.30538899 1
 
0.1%
0.38575774 1
 
0.1%
0.16642161 1
 
0.1%
10.95010641 1
 
0.1%
0.83907023 1
 
0.1%
0.16409983 1
 
0.1%
4.98727953 1
 
0.1%
0.60971407 1
 
0.1%
0.10454741 1
 
0.1%
Other values (990) 990
99.0%
2023-12-09T21:16:45.328249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1780
17.4%
1 1035
10.1%
. 1000
9.8%
9 948
9.3%
3 870
8.5%
2 840
8.2%
5 782
7.6%
4 759
7.4%
7 751
7.3%
6 745
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9234
90.2%
Other Punctuation 1000
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1780
19.3%
1 1035
11.2%
9 948
10.3%
3 870
9.4%
2 840
9.1%
5 782
8.5%
4 759
8.2%
7 751
8.1%
6 745
8.1%
8 724
7.8%
Other Punctuation
ValueCountFrequency (%)
. 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10234
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1780
17.4%
1 1035
10.1%
. 1000
9.8%
9 948
9.3%
3 870
8.5%
2 840
8.2%
5 782
7.6%
4 759
7.4%
7 751
7.3%
6 745
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1780
17.4%
1 1035
10.1%
. 1000
9.8%
9 948
9.3%
3 870
8.5%
2 840
8.2%
5 782
7.6%
4 759
7.4%
7 751
7.3%
6 745
7.3%

areatype
Text

Distinct27
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size64.5 KiB
2023-12-09T21:16:45.576240image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length16
Median length15
Mean length8.889
Min length4

Characters and Unicode

Total characters8889
Distinct characters38
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st rowPlayground
2nd rowPlayground
3rd rowPlayground
4th rowPlayground
5th rowPlayground
ValueCountFrequency (%)
playground 372
29.4%
area 225
17.8%
lawn 124
 
9.8%
sitting 122
 
9.6%
sidewalk 70
 
5.5%
plaza 58
 
4.6%
picnic 32
 
2.5%
general 32
 
2.5%
athletic 25
 
2.0%
entrance 24
 
1.9%
Other values (22) 181
14.3%
2023-12-09T21:16:45.938419image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1063
 
12.0%
n 796
 
9.0%
r 737
 
8.3%
l 621
 
7.0%
g 529
 
6.0%
e 521
 
5.9%
P 515
 
5.8%
d 459
 
5.2%
o 456
 
5.1%
i 446
 
5.0%
Other values (28) 2746
30.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7321
82.4%
Uppercase Letter 1303
 
14.7%
Space Separator 265
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1063
14.5%
n 796
10.9%
r 737
10.1%
l 621
8.5%
g 529
7.2%
e 521
7.1%
d 459
 
6.3%
o 456
 
6.2%
i 446
 
6.1%
u 393
 
5.4%
Other values (12) 1300
17.8%
Uppercase Letter
ValueCountFrequency (%)
P 515
39.5%
A 250
19.2%
S 193
 
14.8%
L 124
 
9.5%
G 49
 
3.8%
B 45
 
3.5%
T 29
 
2.2%
E 24
 
1.8%
W 21
 
1.6%
Q 19
 
1.5%
Other values (5) 34
 
2.6%
Space Separator
ValueCountFrequency (%)
265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8624
97.0%
Common 265
 
3.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1063
12.3%
n 796
 
9.2%
r 737
 
8.5%
l 621
 
7.2%
g 529
 
6.1%
e 521
 
6.0%
P 515
 
6.0%
d 459
 
5.3%
o 456
 
5.3%
i 446
 
5.2%
Other values (27) 2481
28.8%
Common
ValueCountFrequency (%)
265
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8889
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1063
 
12.0%
n 796
 
9.0%
r 737
 
8.3%
l 621
 
7.0%
g 529
 
6.0%
e 521
 
5.9%
P 515
 
5.8%
d 459
 
5.2%
o 456
 
5.1%
i 446
 
5.0%
Other values (28) 2746
30.9%

borough
Text

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T21:16:46.057687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowB
2nd rowB
3rd rowB
4th rowB
5th rowB
ValueCountFrequency (%)
b 603
60.3%
m 322
32.2%
q 57
 
5.7%
r 17
 
1.7%
x 1
 
0.1%
2023-12-09T21:16:46.296408image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 603
60.3%
M 322
32.2%
Q 57
 
5.7%
R 17
 
1.7%
X 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 603
60.3%
M 322
32.2%
Q 57
 
5.7%
R 17
 
1.7%
X 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 603
60.3%
M 322
32.2%
Q 57
 
5.7%
R 17
 
1.7%
X 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 603
60.3%
M 322
32.2%
Q 57
 
5.7%
R 17
 
1.7%
X 1
 
0.1%

cemsdistrict
Text

Distinct40
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size59.7 KiB
2023-12-09T21:16:46.526950image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.022
Min length4

Characters and Unicode

Total characters4022
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.4%

Sample

1st rowB-18
2nd rowB-18
3rd rowB-18
4th rowB-18
5th rowB-18
ValueCountFrequency (%)
m-13 119
 
11.9%
b-03 77
 
7.7%
m-03 68
 
6.8%
b-02 68
 
6.8%
b-01 67
 
6.7%
b-06 52
 
5.2%
b-05 45
 
4.5%
m-12 34
 
3.4%
b-19 33
 
3.3%
b-07 32
 
3.2%
Other values (30) 405
40.5%
2023-12-09T21:16:46.883796image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1000
24.9%
0 608
15.1%
B 603
15.0%
1 538
13.4%
M 322
 
8.0%
3 318
 
7.9%
2 142
 
3.5%
5 86
 
2.1%
4 74
 
1.8%
8 73
 
1.8%
Other values (7) 258
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2000
49.7%
Uppercase Letter 1022
25.4%
Dash Punctuation 1000
24.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 608
30.4%
1 538
26.9%
3 318
15.9%
2 142
 
7.1%
5 86
 
4.3%
4 74
 
3.7%
8 73
 
3.6%
6 65
 
3.2%
9 52
 
2.6%
7 44
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
B 603
59.0%
M 322
31.5%
Q 57
 
5.6%
A 22
 
2.2%
R 17
 
1.7%
X 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3000
74.6%
Latin 1022
 
25.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1000
33.3%
0 608
20.3%
1 538
17.9%
3 318
 
10.6%
2 142
 
4.7%
5 86
 
2.9%
4 74
 
2.5%
8 73
 
2.4%
6 65
 
2.2%
9 52
 
1.7%
Latin
ValueCountFrequency (%)
B 603
59.0%
M 322
31.5%
Q 57
 
5.6%
A 22
 
2.2%
R 17
 
1.7%
X 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4022
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1000
24.9%
0 608
15.1%
B 603
15.0%
1 538
13.4%
M 322
 
8.0%
3 318
 
7.9%
2 142
 
3.5%
5 86
 
2.1%
4 74
 
1.8%
8 73
 
1.8%
Other values (7) 258
 
6.4%

cemsid
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size59.8 KiB
2023-12-09T21:16:47.379416image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.158
Min length1

Characters and Unicode

Total characters4158
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row11316
2nd row1956
3rd row1388
4th row1497
5th row1424
ValueCountFrequency (%)
11089 1
 
0.1%
11165 1
 
0.1%
11079 1
 
0.1%
11137 1
 
0.1%
361 1
 
0.1%
4043 1
 
0.1%
1714 1
 
0.1%
4428 1
 
0.1%
4945 1
 
0.1%
11305 1
 
0.1%
Other values (990) 990
99.0%
2023-12-09T21:16:48.010692image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 945
22.7%
4 535
12.9%
2 518
12.5%
3 370
 
8.9%
6 364
 
8.8%
5 303
 
7.3%
8 288
 
6.9%
9 283
 
6.8%
7 278
 
6.7%
0 274
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4158
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 945
22.7%
4 535
12.9%
2 518
12.5%
3 370
 
8.9%
6 364
 
8.8%
5 303
 
7.3%
8 288
 
6.9%
9 283
 
6.8%
7 278
 
6.7%
0 274
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4158
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 945
22.7%
4 535
12.9%
2 518
12.5%
3 370
 
8.9%
6 364
 
8.8%
5 303
 
7.3%
8 288
 
6.9%
9 283
 
6.8%
7 278
 
6.7%
0 274
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 945
22.7%
4 535
12.9%
2 518
12.5%
3 370
 
8.9%
6 364
 
8.8%
5 303
 
7.3%
8 288
 
6.9%
9 283
 
6.8%
7 278
 
6.7%
0 274
 
6.6%

cemsparent
Text

Distinct357
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Memory size59.8 KiB
2023-12-09T21:16:48.396161image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.104
Min length4

Characters and Unicode

Total characters4104
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique143 ?
Unique (%)14.3%

Sample

1st rowB360
2nd rowB279
3rd rowB342
4th rowB352
5th rowB353
ValueCountFrequency (%)
m010 119
 
11.9%
b073 34
 
3.4%
m058 16
 
1.6%
m037 14
 
1.4%
m081 13
 
1.3%
m029 13
 
1.3%
m088 10
 
1.0%
b251 10
 
1.0%
m042 10
 
1.0%
b032 9
 
0.9%
Other values (347) 752
75.2%
2023-12-09T21:16:48.907944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 750
18.3%
B 623
15.2%
1 490
11.9%
2 437
10.6%
M 322
7.8%
3 321
7.8%
5 190
 
4.6%
4 183
 
4.5%
8 170
 
4.1%
7 162
 
3.9%
Other values (20) 456
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2999
73.1%
Uppercase Letter 1104
 
26.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 623
56.4%
M 322
29.2%
Q 61
 
5.5%
A 22
 
2.0%
R 18
 
1.6%
F 10
 
0.9%
J 7
 
0.6%
D 6
 
0.5%
P 6
 
0.5%
N 5
 
0.5%
Other values (9) 24
 
2.2%
Decimal Number
ValueCountFrequency (%)
0 750
25.0%
1 490
16.3%
2 437
14.6%
3 321
10.7%
5 190
 
6.3%
4 183
 
6.1%
8 170
 
5.7%
7 162
 
5.4%
9 149
 
5.0%
6 147
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3000
73.1%
Latin 1104
 
26.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 623
56.4%
M 322
29.2%
Q 61
 
5.5%
A 22
 
2.0%
R 18
 
1.6%
F 10
 
0.9%
J 7
 
0.6%
D 6
 
0.5%
P 6
 
0.5%
N 5
 
0.5%
Other values (9) 24
 
2.2%
Common
ValueCountFrequency (%)
0 750
25.0%
1 490
16.3%
2 437
14.6%
3 321
10.7%
5 190
 
6.3%
4 183
 
6.1%
8 170
 
5.7%
7 162
 
5.4%
9 149
 
5.0%
6 147
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 750
18.3%
B 623
15.2%
1 490
11.9%
2 437
10.6%
M 322
7.8%
3 321
7.8%
5 190
 
4.6%
4 183
 
4.5%
8 170
 
4.1%
7 162
 
3.9%
Other values (20) 456
11.1%

communityboard
Text

Distinct37
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size58.7 KiB
2023-12-09T21:16:49.143297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row318
2nd row318
3rd row318
4th row318
5th row318
ValueCountFrequency (%)
164 119
 
11.9%
303 77
 
7.7%
302 68
 
6.8%
103 68
 
6.8%
301 67
 
6.7%
306 52
 
5.2%
112 48
 
4.8%
305 45
 
4.5%
355 32
 
3.2%
307 32
 
3.2%
Other values (27) 392
39.2%
2023-12-09T21:16:49.491769image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 804
26.8%
1 710
23.7%
0 609
20.3%
4 246
 
8.2%
6 184
 
6.1%
5 165
 
5.5%
2 144
 
4.8%
8 74
 
2.5%
7 43
 
1.4%
9 21
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 804
26.8%
1 710
23.7%
0 609
20.3%
4 246
 
8.2%
6 184
 
6.1%
5 165
 
5.5%
2 144
 
4.8%
8 74
 
2.5%
7 43
 
1.4%
9 21
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 804
26.8%
1 710
23.7%
0 609
20.3%
4 246
 
8.2%
6 184
 
6.1%
5 165
 
5.5%
2 144
 
4.8%
8 74
 
2.5%
7 43
 
1.4%
9 21
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 804
26.8%
1 710
23.7%
0 609
20.3%
4 246
 
8.2%
6 184
 
6.1%
5 165
 
5.5%
2 144
 
4.8%
8 74
 
2.5%
7 43
 
1.4%
9 21
 
0.7%

councildistrict
Text

Distinct36
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size57.5 KiB
2023-12-09T21:16:49.692630image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.726
Min length1

Characters and Unicode

Total characters1726
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row46
2nd row46
3rd row46
4th row46
5th row46
ValueCountFrequency (%)
6 127
 
12.7%
39 77
 
7.7%
33 70
 
7.0%
35 64
 
6.4%
36 63
 
6.3%
10 48
 
4.8%
2 43
 
4.3%
38 42
 
4.2%
34 42
 
4.2%
42 40
 
4.0%
Other values (26) 384
38.4%
2023-12-09T21:16:50.014934image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 509
29.5%
4 303
17.6%
6 211
12.2%
1 147
 
8.5%
2 123
 
7.1%
5 113
 
6.5%
9 106
 
6.1%
8 82
 
4.8%
0 71
 
4.1%
7 61
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1726
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 509
29.5%
4 303
17.6%
6 211
12.2%
1 147
 
8.5%
2 123
 
7.1%
5 113
 
6.5%
9 106
 
6.1%
8 82
 
4.8%
0 71
 
4.1%
7 61
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1726
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 509
29.5%
4 303
17.6%
6 211
12.2%
1 147
 
8.5%
2 123
 
7.1%
5 113
 
6.5%
9 106
 
6.1%
8 82
 
4.8%
0 71
 
4.1%
7 61
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1726
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 509
29.5%
4 303
17.6%
6 211
12.2%
1 147
 
8.5%
2 123
 
7.1%
5 113
 
6.5%
9 106
 
6.1%
8 82
 
4.8%
0 71
 
4.1%
7 61
 
3.5%

gispropnum
Text

Distinct356
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Memory size59.8 KiB
2023-12-09T21:16:50.392239image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.104
Min length4

Characters and Unicode

Total characters4104
Distinct characters29
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)14.2%

Sample

1st rowB360
2nd rowB279
3rd rowB342
4th rowB352
5th rowB353
ValueCountFrequency (%)
m010 119
 
11.9%
b073 34
 
3.4%
m058 16
 
1.6%
m037 14
 
1.4%
m029 13
 
1.3%
m081 13
 
1.3%
m088 10
 
1.0%
b251 10
 
1.0%
m042 10
 
1.0%
b032 9
 
0.9%
Other values (346) 752
75.2%
2023-12-09T21:16:50.905109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 751
18.3%
B 623
15.2%
1 490
11.9%
2 439
10.7%
M 322
7.8%
3 320
7.8%
5 189
 
4.6%
4 183
 
4.5%
8 170
 
4.1%
7 162
 
3.9%
Other values (19) 455
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3000
73.1%
Uppercase Letter 1104
 
26.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 623
56.4%
M 322
29.2%
Q 61
 
5.5%
A 22
 
2.0%
R 18
 
1.6%
F 10
 
0.9%
J 7
 
0.6%
P 6
 
0.5%
D 6
 
0.5%
N 5
 
0.5%
Other values (9) 24
 
2.2%
Decimal Number
ValueCountFrequency (%)
0 751
25.0%
1 490
16.3%
2 439
14.6%
3 320
10.7%
5 189
 
6.3%
4 183
 
6.1%
8 170
 
5.7%
7 162
 
5.4%
9 149
 
5.0%
6 147
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Common 3000
73.1%
Latin 1104
 
26.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 623
56.4%
M 322
29.2%
Q 61
 
5.5%
A 22
 
2.0%
R 18
 
1.6%
F 10
 
0.9%
J 7
 
0.6%
P 6
 
0.5%
D 6
 
0.5%
N 5
 
0.5%
Other values (9) 24
 
2.2%
Common
ValueCountFrequency (%)
0 751
25.0%
1 490
16.3%
2 439
14.6%
3 320
10.7%
5 189
 
6.3%
4 183
 
6.1%
8 170
 
5.7%
7 162
 
5.4%
9 149
 
5.0%
6 147
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 751
18.3%
B 623
15.2%
1 490
11.9%
2 439
10.7%
M 322
7.8%
3 320
7.8%
5 189
 
4.6%
4 183
 
4.5%
8 170
 
4.1%
7 162
 
3.9%
Other values (19) 455
11.1%

name
Text

Distinct652
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size72.4 KiB
2023-12-09T21:16:51.296097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length62
Median length43
Mean length16.995
Min length4

Characters and Unicode

Total characters16995
Distinct characters72
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique621 ?
Unique (%)62.1%

Sample

1st rowPlayground
2nd rowWilson Playground
3rd row100% Playground
4th rowCurtis Playground
5th rowBergen Beach Playground
ValueCountFrequency (%)
playground 380
 
14.7%
area 206
 
7.9%
sitting 119
 
4.6%
lawn 106
 
4.1%
st 68
 
2.6%
plaza 53
 
2.0%
street 39
 
1.5%
ave 39
 
1.5%
picnic 33
 
1.3%
park 30
 
1.2%
Other values (759) 1519
58.6%
2023-12-09T21:16:51.871116image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1592
 
9.4%
a 1494
 
8.8%
r 1213
 
7.1%
e 1204
 
7.1%
n 1157
 
6.8%
t 942
 
5.5%
o 885
 
5.2%
l 863
 
5.1%
i 726
 
4.3%
P 666
 
3.9%
Other values (62) 6253
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12429
73.1%
Uppercase Letter 2536
 
14.9%
Space Separator 1592
 
9.4%
Decimal Number 278
 
1.6%
Other Punctuation 63
 
0.4%
Dash Punctuation 47
 
0.3%
Close Punctuation 25
 
0.1%
Open Punctuation 25
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1494
12.0%
r 1213
9.8%
e 1204
9.7%
n 1157
9.3%
t 942
 
7.6%
o 885
 
7.1%
l 863
 
6.9%
i 726
 
5.8%
d 633
 
5.1%
g 615
 
4.9%
Other values (16) 2697
21.7%
Uppercase Letter
ValueCountFrequency (%)
P 666
26.3%
S 375
14.8%
A 324
12.8%
L 164
 
6.5%
C 129
 
5.1%
B 113
 
4.5%
M 108
 
4.3%
E 91
 
3.6%
W 89
 
3.5%
T 71
 
2.8%
Other values (16) 406
16.0%
Decimal Number
ValueCountFrequency (%)
1 69
24.8%
2 50
18.0%
0 33
11.9%
7 23
 
8.3%
6 22
 
7.9%
4 21
 
7.6%
9 19
 
6.8%
8 17
 
6.1%
5 15
 
5.4%
3 9
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 27
42.9%
' 15
23.8%
/ 12
19.0%
& 5
 
7.9%
# 3
 
4.8%
% 1
 
1.6%
Space Separator
ValueCountFrequency (%)
1592
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14965
88.1%
Common 2030
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1494
 
10.0%
r 1213
 
8.1%
e 1204
 
8.0%
n 1157
 
7.7%
t 942
 
6.3%
o 885
 
5.9%
l 863
 
5.8%
i 726
 
4.9%
P 666
 
4.5%
d 633
 
4.2%
Other values (42) 5182
34.6%
Common
ValueCountFrequency (%)
1592
78.4%
1 69
 
3.4%
2 50
 
2.5%
- 47
 
2.3%
0 33
 
1.6%
. 27
 
1.3%
) 25
 
1.2%
( 25
 
1.2%
7 23
 
1.1%
6 22
 
1.1%
Other values (10) 117
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16995
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1592
 
9.4%
a 1494
 
8.8%
r 1213
 
7.1%
e 1204
 
7.1%
n 1157
 
6.8%
t 942
 
5.5%
o 885
 
5.2%
l 863
 
5.1%
i 726
 
4.3%
P 666
 
3.9%
Other values (62) 6253
36.8%

omppropid
Text

Distinct460
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Memory size61.3 KiB
2023-12-09T21:16:52.292908image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length4
Mean length5.669
Min length4

Characters and Unicode

Total characters5669
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique194 ?
Unique (%)19.4%

Sample

1st rowB360
2nd rowB279
3rd rowB342
4th rowB352
5th rowB353
ValueCountFrequency (%)
m010-zn20 11
 
1.1%
m010-zn01 9
 
0.9%
m058-zn02 8
 
0.8%
b016 8
 
0.8%
m088 8
 
0.8%
m081-zn01 8
 
0.8%
m010-zn12&13 8
 
0.8%
b087 8
 
0.8%
b111 7
 
0.7%
b077 7
 
0.7%
Other values (450) 918
91.8%
2023-12-09T21:16:52.860137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 964
17.0%
B 621
11.0%
1 613
10.8%
2 560
9.9%
3 381
 
6.7%
M 322
 
5.7%
- 302
 
5.3%
N 290
 
5.1%
Z 285
 
5.0%
4 244
 
4.3%
Other values (22) 1087
19.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3662
64.6%
Uppercase Letter 1674
29.5%
Dash Punctuation 302
 
5.3%
Other Punctuation 31
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 621
37.1%
M 322
19.2%
N 290
17.3%
Z 285
17.0%
Q 61
 
3.6%
A 25
 
1.5%
R 18
 
1.1%
F 10
 
0.6%
J 7
 
0.4%
D 6
 
0.4%
Other values (10) 29
 
1.7%
Decimal Number
ValueCountFrequency (%)
0 964
26.3%
1 613
16.7%
2 560
15.3%
3 381
 
10.4%
4 244
 
6.7%
5 207
 
5.7%
8 183
 
5.0%
7 182
 
5.0%
6 165
 
4.5%
9 163
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 302
100.0%
Other Punctuation
ValueCountFrequency (%)
& 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3995
70.5%
Latin 1674
29.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 621
37.1%
M 322
19.2%
N 290
17.3%
Z 285
17.0%
Q 61
 
3.6%
A 25
 
1.5%
R 18
 
1.1%
F 10
 
0.6%
J 7
 
0.4%
D 6
 
0.4%
Other values (10) 29
 
1.7%
Common
ValueCountFrequency (%)
0 964
24.1%
1 613
15.3%
2 560
14.0%
3 381
 
9.5%
- 302
 
7.6%
4 244
 
6.1%
5 207
 
5.2%
8 183
 
4.6%
7 182
 
4.6%
6 165
 
4.1%
Other values (2) 194
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 964
17.0%
B 621
11.0%
1 613
10.8%
2 560
9.9%
3 381
 
6.7%
M 322
 
5.7%
- 302
 
5.3%
N 290
 
5.1%
Z 285
 
5.0%
4 244
 
4.3%
Other values (22) 1087
19.2%

parkdistrict
Text

Distinct40
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size59.7 KiB
2023-12-09T21:16:53.099622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.022
Min length4

Characters and Unicode

Total characters4022
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.4%

Sample

1st rowB-18
2nd rowB-18
3rd rowB-18
4th rowB-18
5th rowB-18
ValueCountFrequency (%)
m-13 119
 
11.9%
b-03 77
 
7.7%
m-03 68
 
6.8%
b-02 68
 
6.8%
b-01 67
 
6.7%
b-06 52
 
5.2%
b-05 45
 
4.5%
m-12 34
 
3.4%
b-19 33
 
3.3%
b-07 32
 
3.2%
Other values (30) 405
40.5%
2023-12-09T21:16:53.453993image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1000
24.9%
0 608
15.1%
B 603
15.0%
1 538
13.4%
M 322
 
8.0%
3 318
 
7.9%
2 142
 
3.5%
5 86
 
2.1%
4 74
 
1.8%
8 73
 
1.8%
Other values (7) 258
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2000
49.7%
Uppercase Letter 1022
25.4%
Dash Punctuation 1000
24.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 608
30.4%
1 538
26.9%
3 318
15.9%
2 142
 
7.1%
5 86
 
4.3%
4 74
 
3.7%
8 73
 
3.6%
6 65
 
3.2%
9 52
 
2.6%
7 44
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
B 603
59.0%
M 322
31.5%
Q 57
 
5.6%
A 22
 
2.2%
R 17
 
1.7%
X 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3000
74.6%
Latin 1022
 
25.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1000
33.3%
0 608
20.3%
1 538
17.9%
3 318
 
10.6%
2 142
 
4.7%
5 86
 
2.9%
4 74
 
2.5%
8 73
 
2.4%
6 65
 
2.2%
9 52
 
1.7%
Latin
ValueCountFrequency (%)
B 603
59.0%
M 322
31.5%
Q 57
 
5.6%
A 22
 
2.2%
R 17
 
1.7%
X 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4022
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1000
24.9%
0 608
15.1%
B 603
15.0%
1 538
13.4%
M 322
 
8.0%
3 318
 
7.9%
2 142
 
3.5%
5 86
 
2.1%
4 74
 
1.8%
8 73
 
1.8%
Other values (7) 258
 
6.4%

precinct
Text

Distinct50
Distinct (%)5.0%
Missing1
Missing (%)0.1%
Memory size57.7 KiB
2023-12-09T21:16:53.688463image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.006006006
Min length1

Characters and Unicode

Total characters2004
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row69
2nd row69
3rd row69
4th row69
5th row63
ValueCountFrequency (%)
22 119
 
11.9%
90 48
 
4.8%
78 48
 
4.8%
88 46
 
4.6%
75 45
 
4.5%
79 40
 
4.0%
76 39
 
3.9%
81 37
 
3.7%
7 34
 
3.4%
72 33
 
3.3%
Other values (40) 510
51.1%
2023-12-09T21:16:54.053675image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 346
17.3%
7 334
16.7%
8 258
12.9%
1 247
12.3%
6 189
9.4%
9 158
7.9%
0 147
7.3%
3 143
7.1%
5 97
 
4.8%
4 85
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2004
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 346
17.3%
7 334
16.7%
8 258
12.9%
1 247
12.3%
6 189
9.4%
9 158
7.9%
0 147
7.3%
3 143
7.1%
5 97
 
4.8%
4 85
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2004
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 346
17.3%
7 334
16.7%
8 258
12.9%
1 247
12.3%
6 189
9.4%
9 158
7.9%
0 147
7.3%
3 143
7.1%
5 97
 
4.8%
4 85
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2004
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 346
17.3%
7 334
16.7%
8 258
12.9%
1 247
12.3%
6 189
9.4%
9 158
7.9%
0 147
7.3%
3 143
7.1%
5 97
 
4.8%
4 85
 
4.2%

propertyname
Text

Distinct353
Distinct (%)35.3%
Missing1
Missing (%)0.1%
Memory size73.4 KiB
2023-12-09T21:16:54.499025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length41
Median length32
Mean length18.05805806
Min length9

Characters and Unicode

Total characters18040
Distinct characters60
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique140 ?
Unique (%)14.0%

Sample

1st rowRemsen Playground
2nd rowWilson Playground
3rd row100% Playground
4th rowCurtis Playground
5th rowBergen Beach Playground
ValueCountFrequency (%)
park 546
 
20.7%
playground 382
 
14.5%
central 121
 
4.6%
square 34
 
1.3%
prospect 34
 
1.3%
fort 25
 
0.9%
john 22
 
0.8%
triangle 21
 
0.8%
beach 20
 
0.8%
marcus 18
 
0.7%
Other values (499) 1409
53.5%
2023-12-09T21:16:55.108166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 1871
 
10.4%
a 1837
 
10.2%
1633
 
9.1%
n 1133
 
6.3%
e 1105
 
6.1%
o 1077
 
6.0%
P 1047
 
5.8%
l 932
 
5.2%
d 643
 
3.6%
k 641
 
3.6%
Other values (50) 6121
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13588
75.3%
Uppercase Letter 2674
 
14.8%
Space Separator 1633
 
9.1%
Other Punctuation 137
 
0.8%
Dash Punctuation 4
 
< 0.1%
Decimal Number 3
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 1871
13.8%
a 1837
13.5%
n 1133
 
8.3%
e 1105
 
8.1%
o 1077
 
7.9%
l 932
 
6.9%
d 643
 
4.7%
k 641
 
4.7%
u 611
 
4.5%
t 607
 
4.5%
Other values (15) 3131
23.0%
Uppercase Letter
ValueCountFrequency (%)
P 1047
39.2%
C 218
 
8.2%
S 193
 
7.2%
M 119
 
4.5%
B 115
 
4.3%
H 100
 
3.7%
J 98
 
3.7%
G 94
 
3.5%
T 86
 
3.2%
L 84
 
3.1%
Other values (15) 520
19.4%
Other Punctuation
ValueCountFrequency (%)
. 99
72.3%
' 26
 
19.0%
/ 10
 
7.3%
& 1
 
0.7%
% 1
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 2
66.7%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
1633
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16262
90.1%
Common 1778
 
9.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 1871
 
11.5%
a 1837
 
11.3%
n 1133
 
7.0%
e 1105
 
6.8%
o 1077
 
6.6%
P 1047
 
6.4%
l 932
 
5.7%
d 643
 
4.0%
k 641
 
3.9%
u 611
 
3.8%
Other values (40) 5365
33.0%
Common
ValueCountFrequency (%)
1633
91.8%
. 99
 
5.6%
' 26
 
1.5%
/ 10
 
0.6%
- 4
 
0.2%
0 2
 
0.1%
’ 1
 
0.1%
& 1
 
0.1%
1 1
 
0.1%
% 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18039
> 99.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 1871
 
10.4%
a 1837
 
10.2%
1633
 
9.1%
n 1133
 
6.3%
e 1105
 
6.1%
o 1077
 
6.0%
P 1047
 
5.8%
l 932
 
5.2%
d 643
 
3.6%
k 641
 
3.6%
Other values (49) 6120
33.9%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

subpropertyname
Text

MISSING 

Distinct120
Distinct (%)40.1%
Missing701
Missing (%)70.1%
Memory size45.2 KiB
2023-12-09T21:16:55.463649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length40
Median length34
Mean length22.39799331
Min length8

Characters and Unicode

Total characters6697
Distinct characters67
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)15.4%

Sample

1st rowWolfe's Pond Park Zone 3
2nd rowWolfe's Pond Park Zone 2
3rd rowConference House Park Zone 3
4th rowCanarsie Park Zone 1
5th rowCanarsie Park Zone 1
ValueCountFrequency (%)
park 119
 
10.0%
zone 116
 
9.8%
2 45
 
3.8%
1 36
 
3.0%
the 34
 
2.9%
and 30
 
2.5%
fort 23
 
1.9%
hill 22
 
1.9%
3 21
 
1.8%
pond 17
 
1.4%
Other values (188) 726
61.1%
2023-12-09T21:16:55.962389image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
890
 
13.3%
e 645
 
9.6%
r 530
 
7.9%
a 500
 
7.5%
n 403
 
6.0%
o 381
 
5.7%
l 276
 
4.1%
t 269
 
4.0%
s 219
 
3.3%
d 187
 
2.8%
Other values (57) 2397
35.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4529
67.6%
Uppercase Letter 1061
 
15.8%
Space Separator 890
 
13.3%
Decimal Number 129
 
1.9%
Other Punctuation 76
 
1.1%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 184
17.3%
Z 119
11.2%
S 74
 
7.0%
T 73
 
6.9%
C 72
 
6.8%
M 65
 
6.1%
A 61
 
5.7%
H 54
 
5.1%
B 51
 
4.8%
R 47
 
4.4%
Other values (15) 261
24.6%
Lowercase Letter
ValueCountFrequency (%)
e 645
14.2%
r 530
11.7%
a 500
11.0%
n 403
8.9%
o 381
8.4%
l 276
 
6.1%
t 269
 
5.9%
s 219
 
4.8%
d 187
 
4.1%
k 180
 
4.0%
Other values (14) 939
20.7%
Decimal Number
ValueCountFrequency (%)
2 45
34.9%
1 38
29.5%
3 21
16.3%
7 7
 
5.4%
9 6
 
4.7%
6 5
 
3.9%
5 2
 
1.6%
8 2
 
1.6%
4 2
 
1.6%
0 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 25
32.9%
' 17
22.4%
& 14
18.4%
. 14
18.4%
/ 6
 
7.9%
Space Separator
ValueCountFrequency (%)
890
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5590
83.5%
Common 1107
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 645
 
11.5%
r 530
 
9.5%
a 500
 
8.9%
n 403
 
7.2%
o 381
 
6.8%
l 276
 
4.9%
t 269
 
4.8%
s 219
 
3.9%
d 187
 
3.3%
P 184
 
3.3%
Other values (39) 1996
35.7%
Common
ValueCountFrequency (%)
890
80.4%
2 45
 
4.1%
1 38
 
3.4%
, 25
 
2.3%
3 21
 
1.9%
' 17
 
1.5%
& 14
 
1.3%
. 14
 
1.3%
7 7
 
0.6%
9 6
 
0.5%
Other values (8) 30
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6697
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
890
 
13.3%
e 645
 
9.6%
r 530
 
7.9%
a 500
 
7.5%
n 403
 
6.0%
o 381
 
5.7%
l 276
 
4.1%
t 269
 
4.0%
s 219
 
3.3%
d 187
 
2.8%
Other values (57) 2397
35.8%

system
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size73.7 KiB
2023-12-09T21:16:56.241016image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length21
Median length19
Mean length18.331
Min length16

Characters and Unicode

Total characters18331
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st rowB360-EVENTAREA-1
2nd rowB279-EVENTAREA-1956
3rd rowB342-EVENTAREA-1388
4th rowB352-EVENTAREA-1497
5th rowB353-EVENTAREA-1424
ValueCountFrequency (%)
b294-eventarea-2 1
 
0.1%
m010-eventarea-2726 1
 
0.1%
b038-eventarea-4248 1
 
0.1%
m010-eventarea-2629 1
 
0.1%
b073-eventarea-3273 1
 
0.1%
m010-eventarea-2748 1
 
0.1%
b326-eventarea-4408 1
 
0.1%
b049-eventarea-4599 1
 
0.1%
b111-eventarea-4592 1
 
0.1%
m058-eventarea-271 1
 
0.1%
Other values (990) 990
99.0%
2023-12-09T21:16:56.646721image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 3002
16.4%
A 2021
11.0%
- 2000
10.9%
R 1018
 
5.6%
N 1005
 
5.5%
V 1000
 
5.5%
T 1000
 
5.5%
1 989
 
5.4%
0 947
 
5.2%
2 875
 
4.8%
Other values (24) 4474
24.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 10097
55.1%
Decimal Number 6233
34.0%
Dash Punctuation 2000
 
10.9%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 3002
29.7%
A 2021
20.0%
R 1018
 
10.1%
N 1005
 
10.0%
V 1000
 
9.9%
T 1000
 
9.9%
B 624
 
6.2%
M 322
 
3.2%
Q 61
 
0.6%
F 7
 
0.1%
Other values (12) 37
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 989
15.9%
0 947
15.2%
2 875
14.0%
4 683
11.0%
3 646
10.4%
6 466
7.5%
5 452
7.3%
8 405
6.5%
7 391
 
6.3%
9 379
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10098
55.1%
Common 8233
44.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 3002
29.7%
A 2021
20.0%
R 1018
 
10.1%
N 1005
 
10.0%
V 1000
 
9.9%
T 1000
 
9.9%
B 624
 
6.2%
M 322
 
3.2%
Q 61
 
0.6%
F 7
 
0.1%
Other values (13) 38
 
0.4%
Common
ValueCountFrequency (%)
- 2000
24.3%
1 989
12.0%
0 947
11.5%
2 875
10.6%
4 683
 
8.3%
3 646
 
7.8%
6 466
 
5.7%
5 452
 
5.5%
8 405
 
4.9%
7 391
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18331
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 3002
16.4%
A 2021
11.0%
- 2000
10.9%
R 1018
 
5.6%
N 1005
 
5.5%
V 1000
 
5.5%
T 1000
 
5.5%
1 989
 
5.4%
0 947
 
5.2%
2 875
 
4.8%
Other values (24) 4474
24.4%

zipcode
Text

Distinct94
Distinct (%)9.4%
Missing3
Missing (%)0.3%
Memory size60.2 KiB
2023-12-09T21:16:56.928518image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.641925777
Min length2

Characters and Unicode

Total characters4628
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)1.4%

Sample

1st row11236
2nd row11236
3rd row11236
4th row11236
5th row11234
ValueCountFrequency (%)
83 119
 
11.9%
10002 47
 
4.7%
11215 46
 
4.6%
11201 40
 
4.0%
11206 33
 
3.3%
11207 33
 
3.3%
11205 31
 
3.1%
11231 27
 
2.7%
11211 26
 
2.6%
11233 24
 
2.4%
Other values (84) 571
57.3%
2023-12-09T21:16:57.334624image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1845
39.9%
2 870
18.8%
0 735
 
15.9%
3 437
 
9.4%
8 207
 
4.5%
4 127
 
2.7%
5 126
 
2.7%
6 104
 
2.2%
7 101
 
2.2%
9 76
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4628
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1845
39.9%
2 870
18.8%
0 735
 
15.9%
3 437
 
9.4%
8 207
 
4.5%
4 127
 
2.7%
5 126
 
2.7%
6 104
 
2.2%
7 101
 
2.2%
9 76
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4628
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1845
39.9%
2 870
18.8%
0 735
 
15.9%
3 437
 
9.4%
8 207
 
4.5%
4 127
 
2.7%
5 126
 
2.7%
6 104
 
2.2%
7 101
 
2.2%
9 76
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4628
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1845
39.9%
2 870
18.8%
0 735
 
15.9%
3 437
 
9.4%
8 207
 
4.5%
4 127
 
2.7%
5 126
 
2.7%
6 104
 
2.2%
7 101
 
2.2%
9 76
 
1.6%

multipolygon
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2023-12-09T21:16:57.743679image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length61212
Median length4974
Mean length2424.908
Min length168

Characters and Unicode

Total characters2424908
Distinct characters26
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st rowMULTIPOLYGON (((-73.90755064407963 40.6421140304941, -73.90768722069737 40.642025684949104, -73.9075981822017 40.6419493701123, -73.9074756927338 40.64202908911088, -73.90747527830257 40.64204576728657, -73.90755064407963 40.6421140304941)))
2nd rowMULTIPOLYGON (((-73.89543838556742 40.64340280948987, -73.89557152739775 40.64331688409544, -73.89510092194935 40.642891856637235, -73.89497056503872 40.64297515902168, -73.89487344002352 40.643037224988205, -73.89495940386817 40.64311481480156, -73.89497944103489 40.64313290021188, -73.89533065102216 40.64344989506724, -73.89534355672619 40.64346154241669, -73.89534515046144 40.64346298019462, -73.89535036694588 40.643459613399294, -73.89543838556742 40.64340280948987)))
3rd rowMULTIPOLYGON (((-73.89948325486901 40.64627048141331, -73.89945239087007 40.646242886860485, -73.89941852831213 40.64626415811396, -73.89940728011247 40.64627052034469, -73.89903539993304 40.64650411404557, -73.89884635836464 40.64662285778847, -73.89882136025946 40.64663856065173, -73.89884051437971 40.646655621614485, -73.89888570837729 40.646695869508, -73.89893089415344 40.64673611737626, -73.89897607998417 40.64677636522659, -73.89902127532756 40.646816613067294, -73.89906646126725 40.64685686088171, -73.89911165553744 40.64689710868548, -73.89915684158618 40.64693735646411, -73.8991587306811 40.64693904209002, -73.89919012162721 40.646967000090186, -73.89920202768947 40.64697760422473, -73.8992418865718 40.64701310877237, -73.89924722329461 40.64701785917991, -73.89924865266472 40.647018644783664, -73.89925011874115 40.64701939349831, -73.89925161797575 40.64702010622122, -73.8992531527453 40.647020774849906, -73.89925471358073 40.64702140658009, -73.89925629812976 40.64702199330511, -73.89925791583823 40.647022543137936, -73.8992595478007 40.647023048857825, -73.89926121175127 40.64702351048028, -73.89926289114081 40.64702392618979, -73.89926458240888 40.64702430498845, -73.89926629621908 40.647024631576755, -73.89926802191049 40.64702491945313, -73.89926975950223 40.647025156010336, -73.8992715089847 40.64702534755208, -73.89927326917699 40.64702549317669, -73.89927503061956 40.64702559377647, -73.89927679331238 40.647025649351384, -73.89927856435045 40.6470256590071, -73.89928032717921 40.64702562453024, -73.8992820889059 40.64702553692182, -73.89928385068963 40.647025411491605, -73.89928560073083 40.647025232920505, -73.89928734019813 40.64702501021474, -73.89928907618791 40.64702474157946, -73.89929079213607 40.6470244351048, -73.89929249515666 40.64702407728929, -73.89929418524146 40.647023673535934, -73.89929584347145 40.64702322562929, -73.89929749702934 40.647022739896755, -73.89929911873371 40.647022209110375, -73.8993007156755 40.647021635077394, -73.89930228903962 40.647021015997865, -73.89930382817346 40.64702035996705, -73.89930534135296 40.647019666992264, -73.89930682031296 40.64701892986207, -73.89930826385896 40.64701815668011, -73.8993588096758 40.646985313090774, -73.8993867281383 40.64696717226133, -73.89940935427008 40.64695246317445, -73.8994279105492 40.64694040345141, -73.89945989880516 40.64691961953942, -73.8995104432904 40.64688677588203, -73.89956098773537 40.64685392589871, -73.89961154157932 40.64682108220492, -73.8996620870976 40.646788238481555, -73.89971263139326 40.646755388431224, -73.89976317562969 40.6467225446622, -73.89979341930812 40.64670289198875, -73.89981371981641 40.64668970087081, -73.89986426396277 40.646656850753466, -73.89986502226579 40.6466557518807, -73.89986572267536 40.64665462774298, -73.89986637462809 40.64665349275689, -73.89986697813475 40.6466523397182, -73.89986752492891 40.646651162316175, -73.89986802207173 40.64664998216934, -73.89986846130903 40.64664878486224, -73.89986884262862 40.6466475784995, -73.89986917548863 40.64664636308944, -73.89986944924993 40.64664513772219, -73.89986966390862 40.64664390509931, -73.89986983009695 40.6466426706332, -73.89986992890671 40.6466414289043, -73.89986997806245 40.64664018623164, -73.8998699763806 40.64663894351471, -73.89986990849162 40.646637700740165, -73.89986978148784 40.646636458814626, -73.89986960599883 40.64663522495159, -73.89986937138559 40.64663399824114, -73.89986907765477 40.64663277418086, -73.89986873543737 40.646631559083474, -73.89986833527662 40.64663035204039, -73.89986787715907 40.64662916205663, -73.8998673693713 40.64662798193534, -73.89986680362664 40.64662681887343, -73.89986619057503 40.646625666576526, -73.89986551838426 40.64662453133804, -73.89986479887438 40.64662341496916, -73.89986403085364 40.6466223237726, -73.89985420272191 40.646609662930445, -73.89948325486901 40.64627048141331)))
4th rowMULTIPOLYGON (((-73.9175226015395 40.6405821032849, -73.9174809341214 40.64054457398533, -73.9174486281747 40.640563519327706, -73.91687133196716 40.6409020596503, -73.91683813465099 40.640922635015905, -73.91683947846518 40.64092383457829, -73.91686079053818 40.640942877951595, -73.91687468920813 40.64095529804939, -73.91692051942128 40.64099625975016, -73.91696635914806 40.64103722143935, -73.91701218947372 40.64107818310324, -73.91705802931304 40.641119144755514, -73.91710385975011 40.64116010728301, -73.917149699702 40.64120106889837, -73.91719553025278 40.64124203048841, -73.917241369135 40.641282992065996, -73.9172872009805 40.64132395362003, -73.9173160850323 40.64134977335482, -73.91733676048462 40.6413676193916, -73.91733744684058 40.6413680143122, -73.91733814504731 40.64136838582784, -73.91733887519737 40.64136873755503, -73.91733960890741 40.64136907847852, -73.91734036392779 40.64136939420282, -73.91734112252601 40.64136968471518, -73.91734190241783 40.64136996353602, -73.91734269416384 40.64137021625041, -73.91734349657177 40.641370450962036, -73.91734431082483 40.64137066677131, -73.91734512747357 40.641370857367754, -73.91734595596856 40.6413710281613, -73.91734679395218 40.64137117374713, -73.9173476343236 40.64137130042378, -73.9173484841759 40.64137140819636, -73.91734933525164 40.64137148265056, -73.91735018752404 40.641371545398925, -73.91735104928622 40.641371582039035, -73.9173519016144 40.6413715997615, -73.9173527634323 40.6413715913757, -73.9173536252826 40.64137155687486, -73.91735447769888 40.641371503456355, -73.91735532895531 40.64137143202665, -73.91735618024519 40.641371333581375, -73.91735702092781 40.64137120901342, -73.91735786044276 40.641371072737904, -73.9173586881761 40.6413709040352, -73.91735951474283 40.641370722724425, -73.91736033070123 40.64137051619149, -73.91736113486908 40.64137028443555, -73.91736192723079 40.64137004006385, -73.9173627089841 40.64136977046998, -73.91736347776471 40.64136947565228, -73.91736423355582 40.64136916911848, -73.91736497873971 40.64136883646204, -73.91736570148343 40.641368486679575, -73.91741793871128 40.64134241816503, -73.91742394669491 40.64133942375183, -73.91748218358043 40.641310360788545, -73.91754042868148 40.641281305005755, -73.91755529543578 40.64127388728573, -73.91759867374076 40.641252241989235, -73.9176569187482 40.641223179843614, -73.91771515543078 40.64119411676199, -73.9177734003378 40.6411650536567, -73.91783164637629 40.64113599052262, -73.91788988172452 40.64110692735141, -73.91794812766044 40.64107786505864, -73.91797377407337 40.641065068071974, -73.91797846662908 40.64106272646808, -73.9180063723645 40.641048801834984, -73.9180070454425 40.64104845831669, -73.91800769727124 40.64104809046927, -73.91800833492724 40.64104771180551, -73.918008951334 40.64104730881255, -73.91800955475017 40.64104689500414, -73.91801013453617 40.64104647037266, -73.91801069307296 40.64104602141198, -73.91801123625373 40.641045562534664, -73.91801175699425 40.641045086531506, -73.91801225410352 40.64104460060577, -73.91801273703888 40.64104410476423, -73.91801318807663 40.64104359179006, -73.91801361548204 40.64104306979386, -73.9180140192651 40.641042530670944, -73.9180144076821 40.64104198973609, -73.91801476301822 40.64104143256829, -73.91801509471425 40.64104087268205, -73.91801540160345 40.641040297469345, -73.91801567657633 40.641039720432794, -73.91801592555137 40.641039135273104, -73.9180161520762 40.64103854109217, -73.91801635260215 40.64103793968854, -73.91801652948801 40.64103733556652, -73.91801667209091 40.641036731420066, -73.91801678987703 40.64103612005179, -73.9180168757468 40.641035506859666, -73.91801693561655 40.6410348873454, -73.91801697065408 40.64103427321656, -73.91801697259744 40.641033653660976, -73.9180169497086 40.64103303949085, -73.91801690200083 40.641032419899894, -73.9180168211845 40.64103180658896, -73.9180167155415 40.64103119416086, -73.91801658388961 40.64103058261469, -73.91801642030923 40.64102997915045, -73.91801623189437 40.64102938287271, -73.91801600919435 40.6410287883715, -73.9180157723061 40.64102819566125, -73.91801550111718 40.6410276173348, -73.91801520628266 40.64102704079255, -73.9180148866104 40.64102647413834, -73.91801453500953 40.64102591556598, -73.91801416684727 40.64102536598703, -73.9180137667542 40.64102482629099, -73.91801334299893 40.64102430188693, -73.91801289559588 40.641023781068085, -73.91801243279578 40.64102328365173, -73.91801193807383 40.64102278891419, -73.91801142914474 40.64102231127636, -73.91798667705088 40.64100001569093, -73.91796699205192 40.64098228844483, -73.9179225467283 40.64094227279424, -73.91787811091538 40.64090225713297, -73.91783367398241 40.64086223424946, -73.91778923709388 40.640822218552664, -73.91774479199242 40.640782195628525, -73.91770035521048 40.64074217989705, -73.91765591967179 40.64070215784547, -73.91761147472137 40.6406621420734, -73.91756703810823 40.640622119085734, -73.9175226015395 40.6405821032849)))
5th rowMULTIPOLYGON (((-73.91013063084552 40.62231869271989, -73.91008860013173 40.62228077675026, -73.91004618819325 40.62224251826893, -73.91000377747557 40.622204266976894, -73.90996136562583 40.62216601476759, -73.90991896327944 40.622127762549916, -73.90987655271725 40.62208950400635, -73.90983414219401 40.622051252651055, -73.90979173053873 40.622013000378566, -73.90976846966835 40.62199201529942, -73.90976687967574 40.621990581322926, -73.90972841087375 40.62201511372626, -73.90944481938925 40.62219596830169, -73.90920005872646 40.62235205881457, -73.90901716230682 40.622468695540256, -73.90938123140104 40.62279774968793, -73.9098180794464 40.62252915540052, -73.91009971304285 40.62233951199869, -73.91013063084552 40.62231869271989)))
ValueCountFrequency (%)
multipolygon 1000
 
0.8%
40.678726101769534 4
 
< 0.1%
40.71563252307465 4
 
< 0.1%
73.98175650969723 4
 
< 0.1%
40.779955146328696 4
 
< 0.1%
73.97003887032035 4
 
< 0.1%
40.68686194309536 4
 
< 0.1%
73.98100351562084 4
 
< 0.1%
40.67798335099492 4
 
< 0.1%
74.01720748805509 4
 
< 0.1%
Other values (120455) 126510
99.2%
2023-12-09T21:16:58.345551image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 267941
11.0%
4 240451
9.9%
0 218374
9.0%
3 216232
8.9%
9 215835
8.9%
6 203902
8.4%
5 173252
7.1%
8 172930
7.1%
1 160008
6.6%
2 159211
6.6%
Other values (16) 396772
16.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2028136
83.6%
Other Punctuation 188819
 
7.8%
Space Separator 126546
 
5.2%
Dash Punctuation 63273
 
2.6%
Uppercase Letter 12000
 
0.5%
Close Punctuation 3067
 
0.1%
Open Punctuation 3067
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 267941
13.2%
4 240451
11.9%
0 218374
10.8%
3 216232
10.7%
9 215835
10.6%
6 203902
10.1%
5 173252
8.5%
8 172930
8.5%
1 160008
7.9%
2 159211
7.9%
Uppercase Letter
ValueCountFrequency (%)
O 2000
16.7%
L 2000
16.7%
U 1000
8.3%
N 1000
8.3%
G 1000
8.3%
Y 1000
8.3%
P 1000
8.3%
I 1000
8.3%
T 1000
8.3%
M 1000
8.3%
Other Punctuation
ValueCountFrequency (%)
. 126546
67.0%
, 62273
33.0%
Space Separator
ValueCountFrequency (%)
126546
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63273
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3067
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3067
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2412908
99.5%
Latin 12000
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
7 267941
11.1%
4 240451
10.0%
0 218374
9.1%
3 216232
9.0%
9 215835
8.9%
6 203902
8.5%
5 173252
7.2%
8 172930
7.2%
1 160008
6.6%
2 159211
6.6%
Other values (6) 384772
15.9%
Latin
ValueCountFrequency (%)
O 2000
16.7%
L 2000
16.7%
U 1000
8.3%
N 1000
8.3%
G 1000
8.3%
Y 1000
8.3%
P 1000
8.3%
I 1000
8.3%
T 1000
8.3%
M 1000
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2424908
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 267941
11.0%
4 240451
9.9%
0 218374
9.0%
3 216232
8.9%
9 215835
8.9%
6 203902
8.4%
5 173252
7.1%
8 172930
7.1%
1 160008
6.6%
2 159211
6.6%
Other values (16) 396772
16.4%